Andrew G. Barto

ORCID

Publication Activity (10 Years)

Years Active: 1978-2021
Publications (10 Years): 4

Top Venues

ICRA

Int. J. Robotics Res.

Frontiers Neurorobotics

CoRR

Publications

Andrew G. Barto, Richard S. Sutton, Charles W. Anderson
Looking Back on the Actor-Critic Architecture. IEEE Trans. Syst. Man Cybern. Syst. 51 (1) (2021)
Vieri Giuliano Santucci, Pierre-Yves Oudeyer, Andrew G. Barto, Gianluca Baldassarre
Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots. Frontiers Neurorobotics 13 (2019)
Andrew G. Barto
Reinforcement Learning: Connections, Surprises, and Challenge. AI Mag. 40 (1) (2019)
Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill
On Ensuring that Intelligent Machines Are Well-Behaved. CoRR (2017)
Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Sachin Chitta, Bhaskara Marthi, Andrew G. Barto
Learning grounded finite-state representations from unstructured demonstrations. Int. J. Robotics Res. 34 (2) (2015)
Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto
Online Bayesian changepoint detection for articulated motion models. ICRA (2015)
Alec Solway, Carlos Diuk, Natalia Córdova, Debbie Yee, Andrew G. Barto, Yael Niv, Matthew Botvinick
Optimal Behavioral Hierarchy. PLoS Comput. Biol. 10 (8) (2014)
Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto
Learning parameterized motor skills on a humanoid robot. ICRA (2014)
Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
Active Learning of Parameterized Skills. ICML (2014)
Andrew G. Barto
Commentary on Utility and Bounds. Top. Cogn. Sci. 6 (2) (2014)
Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
Variable risk control via stochastic optimization. Int. J. Robotics Res. 32 (7) (2013)
Scott Niekum, Sachin Chitta, Andrew G. Barto, Bhaskara Marthi, Sarah Osentoski
Incremental Semantically Grounded Learning from Demonstration. Robotics: Science and Systems (2013)
Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
Variational Bayesian Optimization for Runtime Risk-Sensitive Control. Robotics: Science and Systems (2012)
William Dabney, Andrew G. Barto
Adaptive Step-Size for Online Temporal Difference Learning. AAAI (2012)
George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
Robot learning from demonstration by constructing skill trees. Int. J. Robotics Res. 31 (3) (2012)
Bruno Castro da Silva, Andrew G. Barto
TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI (2012)
Philip S. Thomas, Andrew G. Barto
Motor primitive discovery. ICDL-EPIROB (2012)
Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto
Learning Parameterized Skills. ICML (2012)
Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto
Learning and generalization of complex tasks from unstructured demonstrations. IROS (2012)
George Dimitri Konidaris, Ilya Scheidwasser, Andrew G. Barto
Transfer in Reinforcement Learning via Shared Features. J. Mach. Learn. Res. 13 (2012)
Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
Learning dynamic arm motions for postural recovery. Humanoids (2011)
Scott Niekum, Lee Spector, Andrew G. Barto
Evolution of reward functions for reinforcement learning. GECCO (Companion) (2011)
Scott Niekum, Andrew G. Barto
Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Lifelong Learning (2011)
Scott Niekum, Andrew G. Barto
Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. NIPS (2011)
George Dimitri Konidaris, Scott Kuindersma, Roderic A. Grupen, Andrew G. Barto
Autonomous Skill Acquisition on a Mobile Manipulator. AAAI (2011)
Philip S. Thomas, Andrew G. Barto
Conjugate Markov Decision Processes. ICML (2011)
Satinder P. Singh, Richard L. Lewis, Andrew G. Barto, Jonathan Sorg
Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective. IEEE Trans. Auton. Ment. Dev. 2 (2) (2010)
Scott Niekum, Andrew G. Barto, Lee Spector
Genetic Programming for Reward Function Search. IEEE Trans. Auton. Ment. Dev. 2 (2) (2010)
Andrew Stout, Andrew G. Barto
Competence progress intrinsic motivation. ICDL (2010)
George Dimitri Konidaris, Scott Kuindersma, Andrew G. Barto, Roderic A. Grupen
Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories. NIPS (2010)
Christopher M. Vigorito, Andrew G. Barto
Intrinsically Motivated Hierarchical Skill Learning in Structured Environments. IEEE Trans. Auton. Ment. Dev. 2 (2) (2010)
George Dimitri Konidaris, Andrew G. Barto
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining. NIPS (2009)
George Dimitri Konidaris, Andrew G. Barto
Efficient Skill Learning using Abstraction Selection. IJCAI (2009)
Özgür Simsek, Andrew G. Barto
Skill Characterization Based on Betweenness. NIPS (2008)
Christopher M. Vigorito, Andrew G. Barto
Hierarchical Representations of Behavior for Efficient Creative Search. AAAI Spring Symposium: Creative Intelligent Systems (2008)
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
Deictic Option Schemas. IJCAI (2007)
George Dimitri Konidaris, Andrew G. Barto
Building Portable Options: Skill Transfer in Reinforcement Learning. IJCAI (2007)
Anders Jonsson, Andrew G. Barto
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes. SARA (2007)
Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf
Repairing Disengagement With Non-Invasive Interventions. AIED (2007)
Andrew G. Barto
Temporal difference learning. Scholarpedia 2 (11) (2007)
Christopher M. Vigorito, Deepak Ganesan, Andrew G. Barto
Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks. SECON (2007)
Michael T. Rosenstein, Andrew G. Barto, Richard E. A. Van Emmerik
Learning at the level of synergies for a robot weightlifter. Robotics Auton. Syst. 54 (8) (2006)
Anders Jonsson, Andrew G. Barto
Causal Graph Based Decomposition of Factored MDPs. J. Mach. Learn. Res. 7 (2006)
George Dimitri Konidaris, Andrew G. Barto
Autonomous shaping: knowledge transfer in reinforcement learning. ICML (2006)
George Dimitri Konidaris, Andrew G. Barto
An Adaptive Robot Motivational System. SAB (2006)
Alicia P. Wolfe, Andrew G. Barto
Decision Tree Methods for Finding Reusable MDP Homomorphisms. AAAI (2006)
Özgür Simsek, Andrew G. Barto
An intrinsic reward mechanism for efficient exploration. ICML (2006)
Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto
Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. Intelligent Tutoring Systems (2006)
Özgür Simsek, Alicia P. Wolfe, Andrew G. Barto
Identifying useful subgoals in reinforcement learning by local graph partitioning. ICML (2005)
Özgür Simsek, Andrew G. Barto
Learning Skills in Reinforcement Learning Using Relative Novelty. SARA (2005)
Anders Jonsson, Andrew G. Barto
A causal approach to hierarchical decomposition of factored MDPs. ICML (2005)
Satinder P. Singh, Andrew G. Barto, Nuttapong Chentanez
Intrinsically Motivated Reinforcement Learning. NIPS (2004)
Michael T. Rosenstein, Andrew G. Barto
Reinforcement learning with supervision by a stable controller. ACC (2004)
Özgür Simsek, Andrew G. Barto
Using relative novelty to identify useful temporal abstractions in reinforcement learning. ICML (2004)
Balaraman Ravindran, Andrew G. Barto
SMDP Homomorphisms: An Algebraic Approach to Abstraction in Semi-Markov Decision Processes. IJCAI (2003)
Andrew G. Barto, Sridhar Mahadevan
Recent Advances in Hierarchical Reinforcement Learning. Discret. Event Dyn. Syst. 13 (1-2) (2003)
Andrew G. Barto, Sridhar Mahadevan
Recent Advances in Hierarchical Reinforcement Learning. Discret. Event Dyn. Syst. 13 (4) (2003)
Balaraman Ravindran, Andrew G. Barto
Relativized Options: Choosing the Right Transformation. ICML (2003)
Michael Kositsky, Andrew G. Barto
The emergence of movement units through learning with noisy efferent signals and delayed sensory feedback. Neurocomputing (2002)
Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts. Mach. Learn. 49 (2-3) (2002)
Marc Pickett, Andrew G. Barto
PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. ICML (2002)
Balaraman Ravindran, Andrew G. Barto
Model Minimization in Hierarchical Reinforcement Learning. SARA (2002)
Theodore J. Perkins, Andrew G. Barto
Lyapunov Design for Safe Reinforcement Learning. J. Mach. Learn. Res. 3 (2002)
Theodore J. Perkins, Andrew G. Barto
Heuristic Search in Infinite State Spaces Guided by Lyapunov Analysis. IJCAI (2001)
Michael Kositsky, Andrew G. Barto
The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. NIPS (2001)
Michael T. Rosenstein, Andrew G. Barto
Robot Weightlifting By Direct Policy Search. IJCAI (2001)
Theodore J. Perkins, Andrew G. Barto
Lyapunov-Constrained Action Sets for Reinforcement Learning. ICML (2001)
Amy McGovern, Andrew G. Barto
Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density. ICML (2001)
Anders Jonsson, Andrew G. Barto
Automated State Abstraction for Options using the U-Tree Algorithm. NIPS (2000)
Robert Moll, Theodore J. Perkins, Andrew G. Barto
Machine Learning for Subproblem Selection. ICML (2000)
Jette Randløv, Andrew G. Barto, Michael T. Rosenstein
Combining Reinforcement Learning with a Local Control Algorithm. ICML (2000)
Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk
A Cerebellar Model of Timing and Prediction in the Control of Reaching. Neural Comput. 11 (3) (1999)
Robert Moll, Andrew G. Barto, Theodore J. Perkins, Richard S. Sutton
Learning Instance-Independent Value Functions to Enhance Local Search. NIPS (1998)
Robert H. Crites, Andrew G. Barto
Elevator Group Control Using Multiple Reinforcement Learning Agents. Mach. Learn. 33 (2-3) (1998)
Richard S. Sutton, Andrew G. Barto
Reinforcement Learning: An Introduction. IEEE Trans. Neural Networks 9 (5) (1998)
Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk
Cerebellar learning for control of a two-link arm in muscle space. ICRA (1997)
Jeffrey F. Monaco, David G. Ward, Andrew G. Barto
Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments. NIPS (1997)
Andrew H. Fagg, Nathan Sitkoff, Andrew G. Barto, James C. Houk
A model of cerebellar learning for control of arm movements using muscle synergies. CIRA (1997)
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein
Reinforcement Learning for Mixed Open-loop and Closed-loop Control. NIPS (1996)
Steven J. Bradtke, Andrew G. Barto
Linear Least-Squares Algorithms for Temporal Difference Learning. Mach. Learn. 22 (1-3) (1996)
Ron Papka, James P. Callan, Andrew G. Barto
Text-Based Information Retrieval Using Exponentiated Gradient Descent. NIPS (1996)
Michael O. Duff, Andrew G. Barto
Local Bandit Approximation for Optimal Learning Problems. NIPS (1996)
Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh
Learning to Act Using Real-Time Dynamic Programming. Artif. Intell. 72 (1-2) (1995)
Andrew G. Barto, James C. Houk
A Predictive Switching Model of Cerebellar Movement Control. NIPS (1995)
Robert H. Crites, Andrew G. Barto
Improving Elevator Performance Using Reinforcement Learning. NIPS (1995)
Robert H. Crites, Andrew G. Barto
An Actor/Critic Algorithm that is Equivalent to Q-Learning. NIPS (1994)
Vijaykumar Gullapalli, Andrew G. Barto, Roderic A. Grupen
Learning Admittance Mappings for Force-Guided Assembly. ICRA (1994)
Andrew G. Barto, Michael O. Duff
Monte Carlo Matrix Inversion and Reinforcement Learning. NIPS (1993)
Satinder P. Singh, Andrew G. Barto, Roderic A. Grupen, Christopher I. Connolly
Robust Reinforcement Learning in Motion Planning. NIPS (1993)
Vijaykumar Gullapalli, Andrew G. Barto
Convergence of Indirect Adaptive Asynchronous Value Iteration Algorithms. NIPS (1993)
Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Machine Learning: From Theory to Applications (1993)
Vijaykumar Gullapalli, Roderic A. Grupen, Andrew G. Barto
Learning reactive admittance control. ICRA (1992)
Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto
Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Cogn. Sci. 15 (2) (1991)
N. E. Berthier, Andrew G. Barto, J. W. Moore
Linear systems analysis of the relationship between firing of deep cerebellar neurons and the classically conditioned nictitating membrane response in rabbits. Biol. Cybern. 65 (2) (1991)
N. E. Berthier, Satinder P. Singh, Andrew G. Barto, James C. Houk
A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm. NIPS (1991)
T. Sinkjaer, C. H. Wu, Andrew G. Barto, James C. Houk
Cerebellar control of endpoint position-a simulation model. IJCNN (1990)
Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew G. Barto
Explaining Temporal Differences to Create Useful Concepts for Evaluating States. AAAI (1990)
Andrew G. Barto, Richard S. Sutton, Christopher J. C. H. Watkins
Sequential Decision Probelms and Neural Networks. NIPS (1989)
Andrew G. Barto, P. Anandan
Pattern-recognizing stochastic learning automata. IEEE Trans. Syst. Man Cybern. 15 (3) (1985)
Oliver G. Selfridge, Richard S. Sutton, Andrew G. Barto
Training and Tracking in Robotics. IJCAI (1985)

Andrew G. Barto.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Andrew G. Barto